Publication | Open Access
Adult-onset genetic leukoencephalopathies: A MRI pattern-based approach in a comprehensive study of 154 patients
73
Citations
22
References
2014
Year
Adult-onset Genetic LeukoencephalopathiesMri Pattern-based ApproachSystematic Biological ScreeningNeurological DisorderCorticobasal DegenerationWhite MatterGenetic EpidemiologyPathologyBrain LesionWhite Matter DiseasesComprehensive StudyNeurologyBrain PathologyNeuropathologyNeuroimagingCerebral Blood FlowImaging GenomicsGenetic DisorderPediatricsMedicine
Inherited white matter diseases are rare and heterogeneous disorders usually encountered in infancy. Adult-onset forms are increasingly recognized. Our objectives were to determine relative frequencies of genetic leukoencephalopathies in a cohort of adult-onset patients and to evaluate the effectiveness of a systematic diagnostic approach. Inclusion criteria of this retrospective study were: (i) symmetrical involvement of white matter on the first available brain MRI; (ii) age of onset above 16 years. Patients with acquired diseases were excluded. Magnetic resonance imaging analysis identified three groups (vascular, cavitary and non-vascular/non-cavitary) in which distinct genetic and/or biochemical testing were realized. One hundred and fifty-four patients (male/female = 60/94) with adult-onset leukoencephalopathies were identified. Mean age of onset was 38.6 years. In the vascular group, 41/55 patients (75%) finally had a diagnosis [including CADASIL (cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy, n = 32) and COL4A1 mutation, n = 7]. In the cavitary group, 13/17 (76%) patients had a diagnosis of EIF2B-related disorder. In the third group (n = 82), a systematic biological screening allowed a diagnosis in 23 patients (28%) and oriented direct genetic screening identified 21 additional diseases (25.6%). Adult-onset genetic leukoencephalopathies are a rare but probably underestimated entity. Our study confirms the use of a magnetic resonance imaging-based classification with a final diagnosis rate of 64% (98/154) cases.
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